Add comprehensive filtering system with hour-based datetime and property filters

This major enhancement addresses user needs for more precise filtering and introduces
powerful new capabilities for property searches:

Key Features:
- Hour-based date filtering (past_hours, datetime_from/to with ISO 8601 support)
- Server-side property filters (beds, baths, sqft, price, lot_sqft, year_built)
- Sorting support (list_date, sold_date, list_price, sqft, beds, baths)
- Full timestamp preservation (YYYY-MM-DD HH:MM:SS instead of date-only)
- Comprehensive validation with helpful error messages

Technical Changes:
- Preserve full datetime precision in processors.py and parsers.py
- Implement client-side hour-based post-filtering for all listing types
- Add server-side GraphQL filters for property characteristics
- Generalize filtering to work across SOLD, PENDING, FOR_SALE, FOR_RENT
- Add 15 comprehensive tests covering all new features
- Maintain full backward compatibility with existing parameters

Fixes #113 (sorting support)

Version bump to 0.7.0 reflects significant new functionality while maintaining
backward compatibility.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

homeharvest/__init__.py

@@ -1,7 +1,7 @@
 import warnings
 import pandas as pd
 from .core.scrapers import ScraperInput
-from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit
+from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit, validate_datetime, validate_filters, validate_sort
 from .core.scrapers.realtor import RealtorScraper
 from .core.scrapers.models import ListingType, SearchPropertyType, ReturnType, Property
 from typing import Union, Optional, List
@@ -15,15 +15,36 @@ def scrape_property(
     mls_only: bool = False,
     past_days: int = None,
     proxy: str = None,
-    date_from: str = None,  #: TODO: Switch to one parameter, Date, with date_from and date_to, pydantic validation
+    date_from: str = None,
     date_to: str = None,
     foreclosure: bool = None,
     extra_property_data: bool = True,
     exclude_pending: bool = False,
-    limit: int = 10000
+    limit: int = 10000,
+    # New date/time filtering parameters
+    past_hours: int = None,
+    datetime_from: str = None,
+    datetime_to: str = None,
+    # New property filtering parameters
+    beds_min: int = None,
+    beds_max: int = None,
+    baths_min: float = None,
+    baths_max: float = None,
+    sqft_min: int = None,
+    sqft_max: int = None,
+    price_min: int = None,
+    price_max: int = None,
+    lot_sqft_min: int = None,
+    lot_sqft_max: int = None,
+    year_built_min: int = None,
+    year_built_max: int = None,
+    # New sorting parameters
+    sort_by: str = None,
+    sort_direction: str = "desc",
 ) -> Union[pd.DataFrame, list[dict], list[Property]]:
     """
     Scrape properties from Realtor.com based on a given location and listing type.
+
     :param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
     :param listing_type: Listing Type (for_sale, for_rent, sold, pending)
     :param return_type: Return type (pandas, pydantic, raw)
@@ -40,10 +61,29 @@ def scrape_property(
     :param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
     :param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
     :param limit: Limit the number of results returned. Maximum is 10,000.
+
+    New parameters:
+    :param past_hours: Get properties in the last _ hours (requires client-side filtering)
+    :param datetime_from, datetime_to: ISO 8601 datetime strings for precise time filtering (e.g. "2025-01-20T14:30:00")
+    :param beds_min, beds_max: Filter by number of bedrooms
+    :param baths_min, baths_max: Filter by number of bathrooms
+    :param sqft_min, sqft_max: Filter by square footage
+    :param price_min, price_max: Filter by listing price
+    :param lot_sqft_min, lot_sqft_max: Filter by lot size
+    :param year_built_min, year_built_max: Filter by year built
+    :param sort_by: Sort results by field (list_date, sold_date, list_price, sqft, beds, baths)
+    :param sort_direction: Sort direction (asc, desc)
     """
     validate_input(listing_type)
     validate_dates(date_from, date_to)
     validate_limit(limit)
+    validate_datetime(datetime_from)
+    validate_datetime(datetime_to)
+    validate_filters(
+        beds_min, beds_max, baths_min, baths_max, sqft_min, sqft_max,
+        price_min, price_max, lot_sqft_min, lot_sqft_max, year_built_min, year_built_max
+    )
+    validate_sort(sort_by, sort_direction)
 
     scraper_input = ScraperInput(
         location=location,
@@ -60,6 +100,26 @@ def scrape_property(
         extra_property_data=extra_property_data,
         exclude_pending=exclude_pending,
         limit=limit,
+        # New date/time filtering
+        past_hours=past_hours,
+        datetime_from=datetime_from,
+        datetime_to=datetime_to,
+        # New property filtering
+        beds_min=beds_min,
+        beds_max=beds_max,
+        baths_min=baths_min,
+        baths_max=baths_max,
+        sqft_min=sqft_min,
+        sqft_max=sqft_max,
+        price_min=price_min,
+        price_max=price_max,
+        lot_sqft_min=lot_sqft_min,
+        lot_sqft_max=lot_sqft_max,
+        year_built_min=year_built_min,
+        year_built_max=year_built_max,
+        # New sorting
+        sort_by=sort_by,
+        sort_direction=sort_direction,
     )
 
     site = RealtorScraper(scraper_input)

homeharvest/core/scrapers/__init__.py

@@ -27,6 +27,29 @@ class ScraperInput(BaseModel):
     limit: int = 10000
     return_type: ReturnType = ReturnType.pandas
 
+    # New date/time filtering parameters
+    past_hours: int | None = None
+    datetime_from: str | None = None
+    datetime_to: str | None = None
+
+    # New property filtering parameters
+    beds_min: int | None = None
+    beds_max: int | None = None
+    baths_min: float | None = None
+    baths_max: float | None = None
+    sqft_min: int | None = None
+    sqft_max: int | None = None
+    price_min: int | None = None
+    price_max: int | None = None
+    lot_sqft_min: int | None = None
+    lot_sqft_max: int | None = None
+    year_built_min: int | None = None
+    year_built_max: int | None = None
+
+    # New sorting parameters
+    sort_by: str | None = None
+    sort_direction: str = "desc"
+
 
 class Scraper:
     session = None
@@ -85,6 +108,29 @@ class Scraper:
         self.limit = scraper_input.limit
         self.return_type = scraper_input.return_type
 
+        # New date/time filtering
+        self.past_hours = scraper_input.past_hours
+        self.datetime_from = scraper_input.datetime_from
+        self.datetime_to = scraper_input.datetime_to
+
+        # New property filtering
+        self.beds_min = scraper_input.beds_min
+        self.beds_max = scraper_input.beds_max
+        self.baths_min = scraper_input.baths_min
+        self.baths_max = scraper_input.baths_max
+        self.sqft_min = scraper_input.sqft_min
+        self.sqft_max = scraper_input.sqft_max
+        self.price_min = scraper_input.price_min
+        self.price_max = scraper_input.price_max
+        self.lot_sqft_min = scraper_input.lot_sqft_min
+        self.lot_sqft_max = scraper_input.lot_sqft_max
+        self.year_built_min = scraper_input.year_built_min
+        self.year_built_max = scraper_input.year_built_max
+
+        # New sorting
+        self.sort_by = scraper_input.sort_by
+        self.sort_direction = scraper_input.sort_direction
+
     def search(self) -> list[Union[Property | dict]]: ...
 
     @staticmethod

homeharvest/core/scrapers/realtor/__init__.py

@@ -132,36 +132,138 @@ class RealtorScraper(Scraper):
         """
 
         date_param = ""
+
+        # Determine date field based on listing type
         if self.listing_type == ListingType.SOLD:
-            if self.date_from and self.date_to:
-                date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
-            elif self.last_x_days:
-                date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
-        elif self.listing_type == ListingType.PENDING:
-            # Skip server-side date filtering for PENDING as both pending_date and contract_date 
+            date_field = "sold_date"
+        elif self.listing_type in [ListingType.FOR_SALE, ListingType.FOR_RENT]:
+            date_field = "list_date"
+        else:  # PENDING
+            # Skip server-side date filtering for PENDING as both pending_date and contract_date
             # filters are broken in the API. Client-side filtering will be applied later.
-            pass
-        else:
-            if self.date_from and self.date_to:
-                date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
+            date_field = None
+
+        # Build date parameter (expand to full days if hour-based filtering is used)
+        if date_field:
+            if self.datetime_from or self.datetime_to:
+                # Hour-based datetime filtering: extract date parts for API, client-side filter by hours
+                from datetime import datetime
+
+                min_date = None
+                max_date = None
+
+                if self.datetime_from:
+                    try:
+                        dt_from = datetime.fromisoformat(self.datetime_from.replace('Z', '+00:00'))
+                        min_date = dt_from.strftime("%Y-%m-%d")
+                    except (ValueError, AttributeError):
+                        pass
+
+                if self.datetime_to:
+                    try:
+                        dt_to = datetime.fromisoformat(self.datetime_to.replace('Z', '+00:00'))
+                        max_date = dt_to.strftime("%Y-%m-%d")
+                    except (ValueError, AttributeError):
+                        pass
+
+                if min_date and max_date:
+                    date_param = f'{date_field}: {{ min: "{min_date}", max: "{max_date}" }}'
+                elif min_date:
+                    date_param = f'{date_field}: {{ min: "{min_date}" }}'
+                elif max_date:
+                    date_param = f'{date_field}: {{ max: "{max_date}" }}'
+
+            elif self.past_hours:
+                # Query API for past N days (minimum 1 day), client-side filter by hours
+                days = max(1, int(self.past_hours / 24) + 1)  # Round up to cover the full period
+                date_param = f'{date_field}: {{ min: "$today-{days}D" }}'
+
+            elif self.date_from and self.date_to:
+                date_param = f'{date_field}: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
             elif self.last_x_days:
-                date_param = f'list_date: {{ min: "$today-{self.last_x_days}D" }}'
+                date_param = f'{date_field}: {{ min: "$today-{self.last_x_days}D" }}'
 
         property_type_param = ""
         if self.property_type:
             property_types = [pt.value for pt in self.property_type]
             property_type_param = f"type: {json.dumps(property_types)}"
 
-        sort_param = (
-            "sort: [{ field: sold_date, direction: desc }]"
-            if self.listing_type == ListingType.SOLD
-            else ""  #: "sort: [{ field: list_date, direction: desc }]"  #: prioritize normal fractal sort from realtor
-        )
+        # Build property filter parameters
+        property_filters = []
+
+        if self.beds_min is not None or self.beds_max is not None:
+            beds_filter = "beds: {"
+            if self.beds_min is not None:
+                beds_filter += f" min: {self.beds_min}"
+            if self.beds_max is not None:
+                beds_filter += f" max: {self.beds_max}"
+            beds_filter += " }"
+            property_filters.append(beds_filter)
+
+        if self.baths_min is not None or self.baths_max is not None:
+            baths_filter = "baths: {"
+            if self.baths_min is not None:
+                baths_filter += f" min: {self.baths_min}"
+            if self.baths_max is not None:
+                baths_filter += f" max: {self.baths_max}"
+            baths_filter += " }"
+            property_filters.append(baths_filter)
+
+        if self.sqft_min is not None or self.sqft_max is not None:
+            sqft_filter = "sqft: {"
+            if self.sqft_min is not None:
+                sqft_filter += f" min: {self.sqft_min}"
+            if self.sqft_max is not None:
+                sqft_filter += f" max: {self.sqft_max}"
+            sqft_filter += " }"
+            property_filters.append(sqft_filter)
+
+        if self.price_min is not None or self.price_max is not None:
+            price_filter = "list_price: {"
+            if self.price_min is not None:
+                price_filter += f" min: {self.price_min}"
+            if self.price_max is not None:
+                price_filter += f" max: {self.price_max}"
+            price_filter += " }"
+            property_filters.append(price_filter)
+
+        if self.lot_sqft_min is not None or self.lot_sqft_max is not None:
+            lot_sqft_filter = "lot_sqft: {"
+            if self.lot_sqft_min is not None:
+                lot_sqft_filter += f" min: {self.lot_sqft_min}"
+            if self.lot_sqft_max is not None:
+                lot_sqft_filter += f" max: {self.lot_sqft_max}"
+            lot_sqft_filter += " }"
+            property_filters.append(lot_sqft_filter)
+
+        if self.year_built_min is not None or self.year_built_max is not None:
+            year_built_filter = "year_built: {"
+            if self.year_built_min is not None:
+                year_built_filter += f" min: {self.year_built_min}"
+            if self.year_built_max is not None:
+                year_built_filter += f" max: {self.year_built_max}"
+            year_built_filter += " }"
+            property_filters.append(year_built_filter)
+
+        property_filters_param = "\n".join(property_filters)
+
+        # Build sort parameter
+        if self.sort_by:
+            sort_param = f"sort: [{{ field: {self.sort_by}, direction: {self.sort_direction} }}]"
+        elif self.listing_type == ListingType.SOLD:
+            sort_param = "sort: [{ field: sold_date, direction: desc }]"
+        else:
+            sort_param = ""  #: prioritize normal fractal sort from realtor
 
         pending_or_contingent_param = (
             "or_filters: { contingent: true, pending: true }" if self.listing_type == ListingType.PENDING else ""
         )
 
+        # Build bucket parameter (only use fractal sort if no custom sort is specified)
+        bucket_param = ""
+        if not self.sort_by:
+            bucket_param = 'bucket: { sort: "fractal_v1.1.3_fr" }'
+
         listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
         is_foreclosure = ""
 
@@ -187,6 +289,7 @@ class RealtorScraper(Scraper):
                                 %s
                                 %s
                                 %s
+                                %s
                             }
                             %s
                             limit: 200
@@ -197,6 +300,7 @@ class RealtorScraper(Scraper):
                 listing_type.value.lower(),
                 date_param,
                 property_type_param,
+                property_filters_param,
                 pending_or_contingent_param,
                 sort_param,
                 GENERAL_RESULTS_QUERY,
@@ -220,8 +324,9 @@ class RealtorScraper(Scraper):
                                         %s
                                         %s
                                         %s
+                                        %s
                                     }
-                                    bucket: { sort: "fractal_v1.1.3_fr" }
+                                    %s
                                     %s
                                     limit: 200
                                     offset: $offset
@@ -231,7 +336,9 @@ class RealtorScraper(Scraper):
                 listing_type.value.lower(),
                 date_param,
                 property_type_param,
+                property_filters_param,
                 pending_or_contingent_param,
+                bucket_param,
                 sort_param,
                 GENERAL_RESULTS_QUERY,
             )
@@ -382,13 +489,111 @@ class RealtorScraper(Scraper):
             for future in as_completed(futures):
                 homes.extend(future.result()["properties"])
 
+        # Apply client-side hour-based filtering if needed
+        # (API only supports day-level filtering, so we post-filter for hour precision)
+        if self.past_hours or self.datetime_from or self.datetime_to:
+            homes = self._apply_hour_based_date_filter(homes)
         # Apply client-side date filtering for PENDING properties
         # (server-side filters are broken in the API)
-        if self.listing_type == ListingType.PENDING and (self.last_x_days or self.date_from):
+        elif self.listing_type == ListingType.PENDING and (self.last_x_days or self.date_from):
             homes = self._apply_pending_date_filter(homes)
-        
+
         return homes
 
+    def _apply_hour_based_date_filter(self, homes):
+        """Apply client-side hour-based date filtering for all listing types.
+
+        This is used when past_hours, datetime_from, or datetime_to are specified,
+        since the API only supports day-level filtering.
+        """
+        if not homes:
+            return homes
+
+        from datetime import datetime, timedelta
+
+        # Determine date range with hour precision
+        date_range = None
+
+        if self.past_hours:
+            cutoff_datetime = datetime.now() - timedelta(hours=self.past_hours)
+            date_range = {'type': 'since', 'date': cutoff_datetime}
+        elif self.datetime_from or self.datetime_to:
+            try:
+                from_datetime = None
+                to_datetime = None
+
+                if self.datetime_from:
+                    from_datetime_str = self.datetime_from.replace('Z', '+00:00') if self.datetime_from.endswith('Z') else self.datetime_from
+                    from_datetime = datetime.fromisoformat(from_datetime_str).replace(tzinfo=None)
+
+                if self.datetime_to:
+                    to_datetime_str = self.datetime_to.replace('Z', '+00:00') if self.datetime_to.endswith('Z') else self.datetime_to
+                    to_datetime = datetime.fromisoformat(to_datetime_str).replace(tzinfo=None)
+
+                if from_datetime and to_datetime:
+                    date_range = {'type': 'range', 'from_date': from_datetime, 'to_date': to_datetime}
+                elif from_datetime:
+                    date_range = {'type': 'since', 'date': from_datetime}
+                elif to_datetime:
+                    date_range = {'type': 'until', 'date': to_datetime}
+            except (ValueError, AttributeError):
+                return homes  # If parsing fails, return unfiltered
+
+        if not date_range:
+            return homes
+
+        # Determine which date field to use based on listing type
+        date_field_name = self._get_date_field_for_listing_type()
+
+        filtered_homes = []
+
+        for home in homes:
+            # Extract the appropriate date for this property
+            property_date = self._extract_date_from_home(home, date_field_name)
+
+            # Handle properties without dates
+            if property_date is None:
+                # For PENDING, include contingent properties without pending_date
+                if self.listing_type == ListingType.PENDING and self._is_contingent(home):
+                    filtered_homes.append(home)
+                continue
+
+            # Check if property date falls within the specified range
+            if self._is_datetime_in_range(property_date, date_range):
+                filtered_homes.append(home)
+
+        return filtered_homes
+
+    def _get_date_field_for_listing_type(self):
+        """Get the appropriate date field name for the current listing type."""
+        if self.listing_type == ListingType.SOLD:
+            return 'last_sold_date'
+        elif self.listing_type == ListingType.PENDING:
+            return 'pending_date'
+        else:  # FOR_SALE or FOR_RENT
+            return 'list_date'
+
+    def _extract_date_from_home(self, home, date_field_name):
+        """Extract a date field from a home (handles both dict and Property object)."""
+        if isinstance(home, dict):
+            date_value = home.get(date_field_name)
+        else:
+            date_value = getattr(home, date_field_name, None)
+
+        if date_value:
+            return self._parse_date_value(date_value)
+        return None
+
+    def _is_datetime_in_range(self, date_obj, date_range):
+        """Check if a datetime object falls within the specified date range (with hour precision)."""
+        if date_range['type'] == 'since':
+            return date_obj >= date_range['date']
+        elif date_range['type'] == 'until':
+            return date_obj <= date_range['date']
+        elif date_range['type'] == 'range':
+            return date_range['from_date'] <= date_obj <= date_range['to_date']
+        return False
+
     def _apply_pending_date_filter(self, homes):
         """Apply client-side date filtering for PENDING properties based on pending_date field.
         For contingent properties without pending_date, tries fallback date fields."""

homeharvest/core/scrapers/realtor/parsers.py

@@ -250,9 +250,28 @@ def parse_description(result: dict) -> Description | None:
 def calculate_days_on_mls(result: dict) -> Optional[int]:
     """Calculate days on MLS from result data"""
     list_date_str = result.get("list_date")
-    list_date = datetime.strptime(list_date_str.split("T")[0], "%Y-%m-%d") if list_date_str else None
+    list_date = None
+    if list_date_str:
+        try:
+            # Parse full datetime, then use date() for day calculation
+            list_date_str_clean = list_date_str.replace('Z', '+00:00') if list_date_str.endswith('Z') else list_date_str
+            list_date = datetime.fromisoformat(list_date_str_clean).replace(tzinfo=None)
+        except (ValueError, AttributeError):
+            # Fallback for date-only format
+            list_date = datetime.strptime(list_date_str.split("T")[0], "%Y-%m-%d") if "T" in list_date_str else None
+
     last_sold_date_str = result.get("last_sold_date")
-    last_sold_date = datetime.strptime(last_sold_date_str, "%Y-%m-%d") if last_sold_date_str else None
+    last_sold_date = None
+    if last_sold_date_str:
+        try:
+            last_sold_date_str_clean = last_sold_date_str.replace('Z', '+00:00') if last_sold_date_str.endswith('Z') else last_sold_date_str
+            last_sold_date = datetime.fromisoformat(last_sold_date_str_clean).replace(tzinfo=None)
+        except (ValueError, AttributeError):
+            # Fallback for date-only format
+            try:
+                last_sold_date = datetime.strptime(last_sold_date_str, "%Y-%m-%d")
+            except ValueError:
+                last_sold_date = None
     today = datetime.now()
 
     if list_date:

homeharvest/core/scrapers/realtor/processors.py

@@ -121,10 +121,10 @@ def process_property(result: dict, mls_only: bool = False, extra_property_data:
         list_price=result["list_price"],
         list_price_min=result["list_price_min"],
         list_price_max=result["list_price_max"],
-        list_date=(datetime.fromisoformat(result["list_date"].split("T")[0]) if result.get("list_date") else None),
+        list_date=(datetime.fromisoformat(result["list_date"].replace('Z', '+00:00') if result["list_date"].endswith('Z') else result["list_date"]) if result.get("list_date") else None),
         prc_sqft=result.get("price_per_sqft"),
-        last_sold_date=(datetime.fromisoformat(result["last_sold_date"]) if result.get("last_sold_date") else None),
-        pending_date=(datetime.fromisoformat(result["pending_date"].split("T")[0]) if result.get("pending_date") else None),
+        last_sold_date=(datetime.fromisoformat(result["last_sold_date"].replace('Z', '+00:00') if result["last_sold_date"].endswith('Z') else result["last_sold_date"]) if result.get("last_sold_date") else None),
+        pending_date=(datetime.fromisoformat(result["pending_date"].replace('Z', '+00:00') if result["pending_date"].endswith('Z') else result["pending_date"]) if result.get("pending_date") else None),
         new_construction=result["flags"].get("is_new_construction") is True,
         hoa_fee=(result["hoa"]["fee"] if result.get("hoa") and isinstance(result["hoa"], dict) else None),
         latitude=(result["location"]["address"]["coordinate"].get("lat") if able_to_get_lat_long else None),

homeharvest/utils.py

@@ -119,10 +119,10 @@ def process_result(result: Property) -> pd.DataFrame:
     prop_data["nearby_schools"] = filter(None, prop_data["nearby_schools"]) if prop_data["nearby_schools"] else None
     prop_data["nearby_schools"] = ", ".join(set(prop_data["nearby_schools"])) if prop_data["nearby_schools"] else None
     
-    # Convert datetime objects to strings for CSV
+    # Convert datetime objects to strings for CSV (preserve full datetime including time)
     for date_field in ["list_date", "pending_date", "last_sold_date"]:
         if prop_data.get(date_field):
-            prop_data[date_field] = prop_data[date_field].strftime("%Y-%m-%d") if hasattr(prop_data[date_field], 'strftime') else prop_data[date_field]
+            prop_data[date_field] = prop_data[date_field].strftime("%Y-%m-%d %H:%M:%S") if hasattr(prop_data[date_field], 'strftime') else prop_data[date_field]
     
     # Convert HttpUrl objects to strings for CSV
     if prop_data.get("property_url"):
@@ -179,3 +179,65 @@ def validate_limit(limit: int) -> None:
 
     if limit is not None and (limit < 1 or limit > 10000):
         raise ValueError("Property limit must be between 1 and 10,000.")
+
+
+def validate_datetime(datetime_str: str | None) -> None:
+    """Validate ISO 8601 datetime format."""
+    if not datetime_str:
+        return
+
+    try:
+        # Try parsing as ISO 8601 datetime
+        datetime.fromisoformat(datetime_str.replace('Z', '+00:00'))
+    except (ValueError, AttributeError):
+        raise InvalidDate(
+            f"Invalid datetime format: '{datetime_str}'. "
+            f"Expected ISO 8601 format (e.g., '2025-01-20T14:30:00' or '2025-01-20')."
+        )
+
+
+def validate_filters(
+    beds_min: int | None = None,
+    beds_max: int | None = None,
+    baths_min: float | None = None,
+    baths_max: float | None = None,
+    sqft_min: int | None = None,
+    sqft_max: int | None = None,
+    price_min: int | None = None,
+    price_max: int | None = None,
+    lot_sqft_min: int | None = None,
+    lot_sqft_max: int | None = None,
+    year_built_min: int | None = None,
+    year_built_max: int | None = None,
+) -> None:
+    """Validate that min values are less than max values for range filters."""
+    ranges = [
+        ("beds", beds_min, beds_max),
+        ("baths", baths_min, baths_max),
+        ("sqft", sqft_min, sqft_max),
+        ("price", price_min, price_max),
+        ("lot_sqft", lot_sqft_min, lot_sqft_max),
+        ("year_built", year_built_min, year_built_max),
+    ]
+
+    for name, min_val, max_val in ranges:
+        if min_val is not None and max_val is not None and min_val > max_val:
+            raise ValueError(f"{name}_min ({min_val}) cannot be greater than {name}_max ({max_val}).")
+
+
+def validate_sort(sort_by: str | None, sort_direction: str | None = "desc") -> None:
+    """Validate sort parameters."""
+    valid_sort_fields = ["list_date", "sold_date", "list_price", "sqft", "beds", "baths"]
+    valid_directions = ["asc", "desc"]
+
+    if sort_by and sort_by not in valid_sort_fields:
+        raise ValueError(
+            f"Invalid sort_by value: '{sort_by}'. "
+            f"Valid options: {', '.join(valid_sort_fields)}"
+        )
+
+    if sort_direction and sort_direction not in valid_directions:
+        raise ValueError(
+            f"Invalid sort_direction value: '{sort_direction}'. "
+            f"Valid options: {', '.join(valid_directions)}"
+        )